A Non-interventional Clinical Trial Assessing Immune Responses After Radiofrequency Ablation of Liver Metastases From Colorectal Cancer.

Background: Radiofrequency ablation (RFA) is an established treatment option for malignancies located in the liver. RFA-induced irreversible coagulation necrosis leads to the release of danger signals and cellular content. Hence, RFA may constitute an endogenous in situ tumor vaccination, stimulating innate and adaptive immune responses, including tumor-antigen specific T cells. This may explain a phenomenon termed abscopal effect, namely tumor regression in untreated lesions evidenced after distant thermal ablation or irradiation. In this study, we therefore assessed systemic and local immune responses in individual patients treated with RFA. Methods: For this prospective clinical trial, patients with liver metastasis from colorectal carcinoma (mCRC) receiving RFA and undergoing metachronous liver surgery for another lesion were recruited (n = 9) during a 5-year period. Tumor and non-malignant liver tissue samples from six patients were investigated by whole transcriptome sequencing and tandem-mass spectrometry, characterizing naturally presented HLA ligands. Tumor antigen-derived HLA-restricted peptides were selected by different predefined approaches. Further, candidate HLA ligands were manually curated. Peripheral blood mononuclear cells were stimulated in vitro with epitope candidate peptides, and functional T cell responses were assessed by intracellular cytokine staining. Immunohistochemical markers were additionally investigated in surgically resected mCRC from patients treated with (n = 9) or without RFA (n = 7). Results: In all six investigated patients, either induced immune responses and/or pre-existing T cell immunity against the selected targets were observed. Multi-cytokine responses were inter alia directed against known tumor antigens such as cyclin D1 but also against a (predicted) mutation contained in ERBB3. Immunohistochemistry did not show a relevant influx of immune cells into distant malignant lesions after RFA treatment (n = 9) as compared to the surgery only mCRC group (n = 7). Conclusions: Using an individualized approach for target selection, RFA induced and/or boosted T cell responses specific for individual tumor antigens were more frequently detectable as compared to previously published observations with well-characterized tumor antigens. However, the witnessed modest RFA-induced immunological effects alone may not be sufficient for the rejection of established tumors. Therefore, these findings warrant further clinical investigation including the assessment of RFA combination therapies e.g., with immune stimulatory agents, cancer vaccination, and/or immune checkpoint inhibitors.

Transcriptional response of Escherichia coli to ammonia and glucose fluctuations.

In large-scale production processes, metabolic control is typically achieved by limited supply of essential nutrients such as glucose or ammonia. With increasing bioreactor dimensions, microbial producers such as Escherichia coli are exposed to changing substrate availabilities due to limited mixing. In turn, cells sense and respond to these dynamic conditions leading to frequent activation of their regulatory programmes. Previously, we characterized short- and long-term strategies of cells to adapt to glucose fluctuations. Here, we focused on fluctuating ammonia supply while studying a continuously running two-compartment bioreactor system comprising a stirred tank reactor (STR) and a plug-flow reactor (PFR). The alarmone ppGpp rapidly accumulated in PFR, initiating considerable transcriptional responses after 70 s. About 400 genes were repeatedly switched on/off when E. coli returned to the STR. E. coli revealed highly diverging long-term transcriptional responses in ammonia compared to glucose fluctuations. In contrast, the induction of stringent regulation was a common feature of both short-term responses. Cellular ATP demands for coping with fluctuating ammonia supply were found to increase maintenance by 15%. The identification of genes contributing to the increased ATP demand together with the elucidation of regulatory mechanisms may help to create robust cells and processes for large-scale application.

Switching between nitrogen and glucose limitation: Unraveling transcriptional dynamics in Escherichia coli.

Transcriptional control under nitrogen and carbon-limitation conditions have been well analyzed for Escherichia coli. However, the transcriptional dynamics that underlie the shift in regulatory programs from nitrogen to carbon limitation is not well studied. In the present study, cells were cultivated at steady state under nitrogen (ammonia)-limited conditions then shifted to carbon (glucose) limitation to monitor changes in transcriptional dynamics. Nitrogen limitation was found to be dominated by sigma 54 (RpoN) and sigma 38 (RpoS), whereas the "housekeeping" sigma factor 70 (RpoD) and sigma 38 regulate cellular status under glucose limitation. During the transition, nitrogen-mediated control was rapidly redeemed and mRNAs that encode active uptake systems, such as ptsG and manXYZ, were quickly amplified. Next, genes encoding facilitators such as lamB were overexpressed, followed by high affinity uptake systems such as mglABC and non-specific porins such as ompF. These regulatory programs are complex and require well-equilibrated and superior control. At the metabolome level, 2-oxoglutarate is the likely component that links carbon- and nitrogen-mediated regulation by interacting with major regulatory elements. In the case of dual glucose and ammonia limitation, sigma 24 (RpoE) appears to play a key role in orchestrating these complex regulatory networks.

Rapid Sampling of Escherichia coli After Changing Oxygen Conditions Reveals Transcriptional Dynamics.

Escherichia coli is able to shift between anaerobic and aerobic metabolism by adapting its gene expression, e.g., of metabolic genes, to the new environment. The dynamics of gene expression that result from environmental shifts are limited, amongst others, by the time needed for regulation and transcription elongation. In this study, we examined gene expression dynamics after an anaerobic-to-aerobic shift on a short time scale (0.5, 1, 2, 5, and 10 min) by RNA sequencing with emphasis on delay times and transcriptional elongation rates (TER). Transient expression patterns and timing of differential expression, characterized by delay and elongation, were identified as key features of the dataset. Gene ontology enrichment analysis revealed early upregulation of respiratory and iron-related gene sets. We inferred specific TERs of 89 operons with a mean TER of 42.0 nt/s and mean delay time of 22.4 s. TERs correlate with sequence features, such as codon bias, whereas delay times correlate with the involvement of regulators. The presented data illustrate that at very short times after a shift in oxygenation, extensional changes of the transcriptome, such as temporary responses, can be observed. Besides regulation, TERs contribute to the dynamics of gene expression.

Origin of modern syphilis and emergence of a pandemic Treponema pallidum cluster.

The abrupt onslaught of the syphilis pandemic that started in the late fifteenth century established this devastating infectious disease as one of the most feared in human history1. Surprisingly, despite the availability of effective antibiotic treatment since the mid-twentieth century, this bacterial infection, which is caused by Treponema pallidum subsp. pallidum (TPA), has been re-emerging globally in the last few decades with an estimated 10.6 million cases in 2008 (ref. 2). Although resistance to penicillin has not yet been identified, an increasing number of strains fail to respond to the second-line antibiotic azithromycin3. Little is known about the genetic patterns in current infections or the evolutionary origins of the disease due to the low quantities of treponemal DNA in clinical samples and difficulties in cultivating the pathogen4. Here, we used DNA capture and whole-genome sequencing to successfully interrogate genome-wide variation from syphilis patient specimens, combined with laboratory samples of TPA and two other subspecies. Phylogenetic comparisons based on the sequenced genomes indicate that the TPA strains examined share a common ancestor after the fifteenth century, within the early modern era. Moreover, most contemporary strains are azithromycin-resistant and are members of a globally dominant cluster, named here as SS14-Ω. The cluster diversified from a common ancestor in the mid-twentieth century subsequent to the discovery of antibiotics. Its recent phylogenetic divergence and global presence point to the emergence of a pandemic strain cluster.

Engineering E. coli for large-scale production - Strategies considering ATP expenses and transcriptional responses.

Microbial producers such as Escherichia coli are evolutionarily trained to adapt to changing substrate availabilities. Being exposed to large-scale production conditions, their complex, multilayered regulatory programs are frequently activated because they face changing substrate supply due to limited mixing. Here, we show that E. coli can adopt both short- and long-term strategies to withstand these stress conditions. Experiments in which glucose availability was changed over a short time scale were performed in a two-compartment bioreactor system. Quick metabolic responses were observed during the first 30s of glucose shortage, and after 70s, fundamental transcriptional programs were initiated. Since cells are fluctuating under simulated large-scale conditions, this scenario represents a continuous on/off switching of about 600 genes. Furthermore, the resulting ATP maintenance demands were increased by about 40-50%, allowing us to conclude that hyper-producing strains could become ATP-limited under large-scale production conditions. Based on the observed transcriptional patterns, we identified a number of candidate gene deletions that may reduce unwanted ATP losses. In summary, we present a theoretical framework that provides biological targets that could be used to engineer novel E. coli strains such that large-scale performance equals laboratory-scale expectations.

EAGER: efficient ancient genome reconstruction.

BACKGROUND: The automated reconstruction of genome sequences in ancient genome analysis is a multifaceted process. RESULTS: Here we introduce EAGER, a time-efficient pipeline, which greatly simplifies the analysis of large-scale genomic data sets. EAGER provides features to preprocess, map, authenticate, and assess the quality of ancient DNA samples. Additionally, EAGER comprises tools to genotype samples to discover, filter, and analyze variants. CONCLUSIONS: EAGER encompasses both state-of-the-art tools for each step as well as new complementary tools tailored for ancient DNA data within a single integrated solution in an easily accessible format.

MALT1 Protease Activity Controls the Expression of Inflammatory Genes in Keratinocytes upon Zymosan Stimulation.

The protease activity of the paracaspase mucosa-associated lymphoid tissue lymphoma translocation gene 1 (MALT1) plays an important role in antigen receptor-mediated lymphocyte activation by controlling the activity of the transcription factor nuclear factor-κB and is thus essential for the expression of inflammatory target genes. MALT1 is not only present in cells of the hematopoietic lineage, but is ubiquitously expressed. Here we report that stimulation with zymosan or Staphylococcus aureus induced MALT1 protease activity in human primary keratinocytes. Inhibition of the Src family of kinases or novel protein kinase C isoforms as well as silencing of CARMA2 or BCL10 interfered with activation of MALT1 protease. Silencing or inhibition of MALT1 protease strongly decreased the expression of important inflammatory genes such as TNFα, IL-17C, CXCL8 and HBD-2. MALT1-inhibited cells were unable to mount an antimicrobial response upon zymosan stimulation or phorbolester/ionomycin treatment, demonstrating a central role of MALT1 protease activity in keratinocyte immunity and suggesting MALT1 as a potential target in inflammatory skin diseases.

Resistance to renal denervation therapy - Identification of underlying mechanisms by analysis of differential DNA methylation.

BACKGROUND: Factors causing resistance to renal denervation (RDN) for treatment of arterial hypertension are not known. In the current study, we sought to determine mechanisms involved in responsiveness to renal denervation therapy in patients with difficult-to-control and resistant hypertension. METHODS AND RESULTS: We evaluated the differential CpG methylation of genes in blood samples isolated from patients of a recently described cohort of responders or non-responders to renal denervation using microarray technique and measured protein levels of identified downstream effectors in blood samples of these patients by ELISA. Our analysis revealed up to 6103 methylation sites differing significantly between non-responders and responders to renal denervation therapy. Software based analysis showed several of these loci to be relevant for arterial hypertension and sympathetic nervous activity. Particularly, genes involved in glutamate synthesis, degradation and glutamate signaling pathways were differently methylated between both groups. For instance, genes for glutamate dehydrogenase 1 and 2 central to glutamate metabolism, genes for ionotropic (AMPA, NMDA) and metabotropic glutamate receptors as well as glutamate transporters revealed significant differences in methylation correlating with responsiveness to RDN. To underline their potential relevance for responsiveness to RDN, we measured plasma protein levels of norepinephrine, a downstream effector of the glutamate receptor pathway, which were significantly lower in non-responders to RDN. CONCLUSIONS: The present study describes novel molecular targets potentially contributing to reduction of blood pressure after RDN in some patients. Identifying patients with a high responsiveness to RDN could contribute to an individualized therapy in drug resistant hypertension.

Interferon Kappa Inhibits Human Papillomavirus 31 Transcription by Inducing Sp100 Proteins.

UNLABELLED: High-risk human papillomaviruses (hr-HPV) establish persistent infections in keratinocytes, which can lead to cancer of the anogenital tract. Interferons (IFNs) are a family of secreted cytokines that induce IFN-stimulated genes (ISGs), many of which display antiviral activities. Transcriptome studies have indicated that established hr-HPV-positive cell lines display a reduced expression of ISGs, which correlates with decreased levels of interferon kappa (IFN-κ), a type I IFN constitutively expressed in keratinocytes. Prior studies have also suggested that IFN-ß has anti-hr-HPV activity but the underlying mechanisms are not well understood. The downregulation of IFN-κ by hr-HPV raises the possibility that IFN-κ has anti-HPV activity. Using doxycycline-inducible IFN-κ expression in CIN612-9E cells, which maintain extrachromosomally replicating HPV31 genomes, we demonstrated that IFN-κ inhibits the growth of these cells and reduces viral transcription and replication. Interestingly, the initiation of viral early transcription was already inhibited at 4 to 6 h after IFN-κ expression. This was also observed with recombinant IFN-ß, suggesting a common mechanism of IFNs. Transcriptome sequencing (RNA-seq) analysis identified 1,367 IFN-κ-regulated genes, of which 221 were modulated >2-fold. The majority of those (71%) matched known ISGs, confirming that IFN-κ acts as a bona fide type I IFN in hr-HPV-positive keratinocytes. RNA interference (RNAi) and cotransfection experiments indicated that the inhibition of viral transcription is mainly due to the induction of Sp100 proteins by IFN-κ. Consistent with published data showing that Sp100 acts as a restriction factor for HPV18 infection, our results suggest that hr-HPV target IFN-κ to prevent Sp100 expression and identify Sp100 as an ISG with anti-HPV activity. IMPORTANCE: High-risk HPV can establish persistent infections which may progress to anogenital cancers. hr-HPV interfere with the expression of interferon (IFN)-stimulated genes (ISGs), which is due to reduced levels of IFN-κ, an IFN that is constitutively expressed in human keratinocytes. This study reveals that IFN-κ rapidly inhibits HPV transcription and that this is due to the induction of Sp100 proteins. Thus, Sp100 represents an ISG for hr-HPV.

RNA sequencing analysis identifies novel spliced transcripts but does not indicate quantitative or qualitative changes of viral transcripts during progression of cottontail rabbit papillomavirus-induced tumours.

Persistent infections with high-risk human papillomaviruses (HPVs) can result in the development of cancer of the cervix uteri and other malignancies. The underlying molecular mechanisms leading to the progression of HPV-induced lesions are, however, not well understood. Cottontail rabbit papillomavirus (CRPV) induces papillomas in domestic rabbits which progress at a very high rate to cancer. Using this model, we compared the transcriptional patterns of CRPV in papillomas and carcinomas by RNA sequencing (RNA-seq). The most abundant transcripts can encode E7, short E6 and E1^E4, followed by full-length E6, E2, E1 and E9^E2C. In addition, we identified two rare, novel splice junctions 7810/3714 and 1751/3065 in both papillomas and carcinomas which have been described for other papillomaviruses. Neither RNA-seq nor quantitative real-time PCR-based assays identified qualitative or quantitative changes of viral transcription between papillomas and carcinomas. In summary, our analyses confirmed that papillomaviruses have highly similar transcriptional patterns, but they do not suggest that changes in these patterns contribute to the progression of CRPV-induced tumours.

Parallel detection of ancient pathogens via array-based DNA capture.

DNA capture coupled with next generation sequencing is highly suitable for the study of ancient pathogens. Screening for pathogens can, however, be meticulous when assays are restricted to the enrichment of single organisms, which is common practice. Here, we report on an array-based DNA capture screening technique for the parallel detection of nearly 100 pathogens that could have potentially left behind molecular signatures in preserved ancient tissues. We demonstrate the sensitivity of our method through evaluation of its performance with a library known to harbour ancient Mycobacterium leprae DNA. This rapid and economical technique will be highly useful for the identification of historical diseases that are difficult to characterize based on archaeological information alone.

inPHAP: interactive visualization of genotype and phased haplotype data.

BACKGROUND: To understand individual genomes it is necessary to look at the variations that lead to changes in phenotype and possibly to disease. However, genotype information alone is often not sufficient and additional knowledge regarding the phase of the variation is needed to make correct interpretations. Interactive visualizations, that allow the user to explore the data in various ways, can be of great assistance in the process of making well informed decisions. But, currently there is a lack for visualizations that are able to deal with phased haplotype data. RESULTS: We present inPHAP, an interactive visualization tool for genotype and phased haplotype data. inPHAP features a variety of interaction possibilities such as zooming, sorting, filtering and aggregation of rows in order to explore patterns hidden in large genetic data sets. As a proof of concept, we apply inPHAP to the phased haplotype data set of Phase 1 of the 1000 Genomes Project. Thereby, inPHAP's ability to show genetic variations on the population as well as on the individuals level is demonstrated for several disease related loci. CONCLUSIONS: As of today, inPHAP is the only visual analytical tool that allows the user to explore unphased and phased haplotype data interactively. Due to its highly scalable design, inPHAP can be applied to large datasets with up to 100 GB of data, enabling users to visualize even large scale input data. inPHAP closes the gap between common visualization tools for unphased genotype data and introduces several new features, such as the visualization of phased data. inPHAP is available for download at http://bit.ly/1iJgKmX.

Genome-wide comparison of medieval and modern Mycobacterium leprae.

Leprosy was endemic in Europe until the Middle Ages. Using DNA array capture, we have obtained genome sequences of Mycobacterium leprae from skeletons of five medieval leprosy cases from the United Kingdom, Sweden, and Denmark. In one case, the DNA was so well preserved that full de novo assembly of the ancient bacterial genome could be achieved through shotgun sequencing alone. The ancient M. leprae sequences were compared with those of 11 modern strains, representing diverse genotypes and geographic origins. The comparisons revealed remarkable genomic conservation during the past 1000 years, a European origin for leprosy in the Americas, and the presence of an M. leprae genotype in medieval Europe now commonly associated with the Middle East. The exceptional preservation of M. leprae biomarkers, both DNA and mycolic acids, in ancient skeletons has major implications for palaeomicrobiology and human pathogen evolution.

REVEAL--visual eQTL analytics.

MOTIVATION: The analysis of expression quantitative trait locus (eQTL) data is a challenging scientific endeavor, involving the processing of very large, heterogeneous and complex data. Typical eQTL analyses involve three types of data: sequence-based data reflecting the genotypic variations, gene expression data and meta-data describing the phenotype. Based on these, certain genotypes can be connected with specific phenotypic outcomes to infer causal associations of genetic variation, expression and disease. To this end, statistical methods are used to find significant associations between single nucleotide polymorphisms (SNPs) or pairs of SNPs and gene expression. A major challenge lies in summarizing the large amount of data as well as statistical results and to generate informative, interactive visualizations. RESULTS: We present Reveal, our visual analytics approach to this challenge. We introduce a graph-based visualization of associations between SNPs and gene expression and a detailed genotype view relating summarized patient cohort genotypes with data from individual patients and statistical analyses. AVAILABILITY: Reveal is included in Mayday, our framework for visual exploration and analysis. It is available at http://it.inf.uni-tuebingen.de/software/reveal/. CONTACT: guenter.jaeger@uni-tuebingen.de.

iHAT: interactive hierarchical aggregation table for genetic association data.

In the search for single-nucleotide polymorphisms which influence the observable phenotype, genome wide association studies have become an important technique for the identification of associations between genotype and phenotype of a diverse set of sequence-based data. We present a methodology for the visual assessment of single-nucleotide polymorphisms using interactive hierarchical aggregation techniques combined with methods known from traditional sequence browsers and cluster heatmaps. Our tool, the interactive Hierarchical Aggregation Table (iHAT), facilitates the visualization of multiple sequence alignments, associated metadata, and hierarchical clusterings. Different color maps and aggregation strategies as well as filtering options support the user in finding correlations between sequences and metadata. Similar to other visualizations such as parallel coordinates or heatmaps, iHAT relies on the human pattern-recognition ability for spotting patterns that might indicate correlation or anticorrelation. We demonstrate iHAT using artificial and real-world datasets for DNA and protein association studies as well as expression Quantitative Trait Locus data.

An eQTL biological data visualization challenge and approaches from the visualization community.

In 2011, the IEEE VisWeek conferences inaugurated a symposium on Biological Data Visualization. Like other domain-oriented Vis symposia, this symposium's purpose was to explore the unique characteristics and requirements of visualization within the domain, and to enhance both the Visualization and Bio/Life-Sciences communities by pushing Biological data sets and domain understanding into the Visualization community, and well-informed Visualization solutions back to the Biological community. Amongst several other activities, the BioVis symposium created a data analysis and visualization contest. Unlike many contests in other venues, where the purpose is primarily to allow entrants to demonstrate tour-de-force programming skills on sample problems with known solutions, the BioVis contest was intended to whet the participants' appetites for a tremendously challenging biological domain, and simultaneously produce viable tools for a biological grand challenge domain with no extant solutions. For this purpose expression Quantitative Trait Locus (eQTL) data analysis was selected. In the BioVis 2011 contest, we provided contestants with a synthetic eQTL data set containing real biological variation, as well as a spiked-in gene expression interaction network influenced by single nucleotide polymorphism (SNP) DNA variation and a hypothetical disease model. Contestants were asked to elucidate the pattern of SNPs and interactions that predicted an individual's disease state. 9 teams competed in the contest using a mixture of methods, some analytical and others through visual exploratory methods. Independent panels of visualization and biological experts judged entries. Awards were given for each panel's favorite entry, and an overall best entry agreed upon by both panels. Three special mention awards were given for particularly innovative and useful aspects of those entries. And further recognition was given to entries that correctly answered a bonus question about how a proposed "gene therapy" change to a SNP might change an individual's disease status, which served as a calibration for each approaches' applicability to a typical domain question. In the future, BioVis will continue the data analysis and visualization contest, maintaining the philosophy of providing new challenging questions in open-ended and dramatically underserved Bio/Life Sciences domains.